Optimizing integrated behavioral healthcare implementation in primary care settings using latent class analysis

Abstract

Access to high-quality behavioral health services is a struggle for millions of Americans and an ongoing frustration for many medical and mental health professionals who refer for or provide this care. Over the past several decades, several models of care have been developed in attempts to improve this access, but with varying degrees of success in implementation and dissemination. Integrated behavioral healthcare, or IBH, is an umbrella term for these models, which aim to bring mental health professionals into primary care medical clinics for more direct mental health access. The current research consists of two studies that examine a community sample of 102 primary care medical clinics that were in varying stages of implementation of the IBH practice approach. In the first study, I used latent class analysis to identify classes of clinics based on their implementation of IBH processes and structures and then examined the influence of context variables on the likelihood that an implementation structure will result. Results were four classes of clinics: Low IBH, Structural IBH, Partial IBH, and Strong IBH; Partial IBH clinics tended to be more rural, in smaller organizations, and to serve lower SES-risk patients. There were noticeable differences in levels of implementation for many of the components of IBH, which has implications for supporting current and future IBH implementation projects toward success. In the second study, I explored the possibility that IBH implementation classes moderate health disparities. Results indicated that IBH may improve healthcare management in some disparate situations, but that IBH alone cannot resolve healthcare disparities and is likely only one of many primary care innovations that practices must adopt to address healthcare disparities.